Microplastic Particles Contain Ice Nucleation Sites That Can Be Inhibited by Atmospheric Aging.

Recent research has shown that microplastics are widespread in the atmosphere. However, we know little about their ability to nucleate ice and their impact on ice formation in clouds. Ice nucleation by microplastics could also limit their long-range transport and global distribution. The present study explores the heterogeneous ice-nucleating ability of seven microplastic samples in immersion freezing mode. Two polypropylene samples and one polyethylene terephthalate sample froze heterogeneously with median freezing temperatures of -20.9, -23.2, and -21.9 °C, respectively. The number of ice nucleation sites per surface area, ns(T), ranged from 10-1 to 104 cm-2 in a temperature interval of -15 to -25 °C, which is comparable to that of volcanic ash and fungal spores. After exposure to ozone or a combination of UV light and ozone, simulating atmospheric aging, the ice nucleation activity decreased in some cases and remained unchanged in others. Our freezing data suggest that microplastics may promote ice formation in cloud droplets. In addition, based on a comparison of our freezing results and previous simulations using a global transport model, ice nucleation by microplastics will impact their long-range transport to faraway locations and global distribution.

Professionalization of Clinical Ethics Consultants: A Need for Liability Protection?

Clinical Ethics Consultation (CEC) has grown significantly in the last decade, and efforts are being made to professionalize the practice. The American Society for Bioethics and Humanities (ASBH) has been instrumental in this process, having published the Code of Ethics and Professional Responsibilities for Healthcare Ethics Consultants and founded and endorsed the creation of the Healthcare Ethics Consultant Certified (HCEC) Certification Commission. The ASBH also published "core competencies" for healthcare ethics consultants and has delineated a clear identity and role of such consultants distinct from that other healthcare professionals. In addition, more enter the field armed with advanced degrees (MA and PhD) or certification in clinical ethics consultation. While some have questioned the trend toward professionalization, the momentum is clearly in its favor. This paper explores three questions: Does the professionalization of healthcare ethics consultation expose those engaged in the field to the types of liability claims faced by professionals in other fields? What specific liabilities could affect a healthcare ethics consultant? And finally, what should healthcare ethics consultants do to protect themselves against liability claims? We conclude that while the risk of liability remains low, those engaged in the field should accept that risk just as part of their status as professionals and, like those in allied professions, seek appropriate protection in the form of liability insurance.

Catalyst Aggregation Matters for Immobilized Molecular CO2RR Electrocatalysts.

Here, we detail how the catalytic behavior of immobilized molecular electrocatalysts for the CO2 reduction reaction (CO2RR) can be impacted by catalyst aggregation. Operando Raman spectroscopy was used to study the CO2RR mediated by a layer of cobalt phthalocyanine (CoPc) immobilized on the cathode of an electrochemical flow reactor. We demonstrate that during electrolysis, the oxidation state of CoPc in the catalyst layer is dependent upon the degree of catalyst aggregation. Our data indicate that immobilized molecular catalysts must be dispersed on conductive supports to mitigate the formation of aggregates and produce meaningful performance data. We leveraged insights from this mechanistic study to engineer an improved CO-forming immobilized molecular catalyst─cobalt octaethoxyphthalocyanine (EtO8-CoPc)─that exhibited high selectivity (FECO ≥ 95%), high partial current density (JCO ≥ 300 mA/cm2), and high durability (ΔFECO < 0.1%/h at 150 mA/cm2) in a flow cell. This work demonstrates how to accurately identify CO2RR active species of molecular catalysts using operando Raman spectroscopy and how to use this information to implement improved molecular electrocatalysts into flow cells. This work also shows that the active site of CoPc during CO2RR catalysis in a flow cell is the metal center.

Electronic State Population Dynamics upon Ultrafast Strong Field Ionization and Fragmentation of Molecular Nitrogen.

Air lasing from single ionized N_{2}^{+} molecules induced by laser filamentation in air has been intensively investigated and the mechanisms responsible for lasing are currently highly debated. We use ultrafast nitrogen K-edge spectroscopy to follow the strong field ionization and fragmentation dynamics of N_{2} upon interaction with an ultrashort 800 nm laser pulse. Using probe pulses generated by extreme high-order harmonic generation, we observe transitions indicative of the formation of the electronic ground X^{2}Σ_{g}^{+}, first excited A^{2}Π_{u}, and second excited B^{2}Σ_{u}^{+} states of N_{2}^{+} on femtosecond timescales, from which we can quantitatively determine the time-dependent electronic state population distribution dynamics of N_{2}^{+}. Our results show a remarkably low population of the A^{2}Π_{u} state, and nearly equal populations of the X^{2}Σ_{g}^{+} and B^{2}Σ_{u}^{+} states. In addition, we observe fragmentation of N_{2}^{+} into N and N^{+} on a timescale of several tens of picoseconds that we assign to significant collisional dynamics in the plasma, resulting in dissociative excitation of N_{2}^{+}.

Electrocatalysts Derived from Copper Complexes Transform CO into C2+ Products Effectively in a Flow Cell.

Electrochemical reactors that electrolytically convert CO2 into higher-value chemicals and fuels often pass a concentrated hydroxide electrolyte across the cathode. This strongly alkaline medium converts the majority of CO2 into unreactive HCO3 - and CO3 2- byproducts rather than into CO2 reduction reaction (CO2RR) products. The electrolysis of CO (instead of CO2 ) does not suffer from this undesirable reaction chemistry because CO does not react with OH- . Moreover, CO can be more readily reduced into products containing two or more carbon atoms (i. e., C2+ products) compared to CO2 . We demonstrate here that an electrocatalyst layer derived from copper phthalocyanine (CuPc) mediates this conversion effectively in a flow cell. This catalyst achieved a 25 % higher selectivity for acetate formation at 200 mA/cm2 than a known state-of-art oxide-derived Cu catalyst tested in the same flow cell. A gas diffusion electrode coated with CuPc electrolyzed CO into C2+ products at high rates of product formation (i. e., current densities ≥200 mA/cm2 ), and at high faradaic efficiencies for C2+ production (FEC2+ ; >70 % at 200 mA/cm2 ). While operando Raman spectroscopy did not reveal evidence of structural changes to the copper molecular complex, X-ray photoelectron spectroscopy suggests that the catalyst undergoes conversion to a metallic copper species during catalysis. Notwithstanding, the ligand environment about the metal still impacts catalysis, which we demonstrated through the study of a homologous CuPc bearing ethoxy substituents. These findings reveal new strategies for using metal complexes for the formation of carbon-neutral chemicals and fuels at industrially relevant conditions.

A quantum molecular movie: polyad predissociation dynamics in the VUV excited 3pσ2Σu state of NO2.

The optical formation of coherent superposition states, a wavepacket, can allow the study of zeroth-order states, the evolution of which exhibit structural and electronic changes as a function of time: this leads to the notion of a molecular movie. Intramolecular vibrational energy redistribution, due to anharmonic coupling between modes, is the molecular movie considered here. There is no guarantee, however, that the formed superposition will behave semi-classically (e.g. Gaussian wavepacket dynamics) or even as an intuitively useful zeroth-order state. Here we present time-resolved photoelectron spectroscopy (TRPES) studies of an electronically excited triatomic molecule wherein the vibrational dynamics must be treated quantum mechanically and the simple picture of population flow between coupled normal modes fails. Specifically, we report on vibronic wavepacket dynamics in the zeroth-order 3pσ2Σu Rydberg state of NO2. This wavepacket exemplifies two general features of excited state dynamics in polyatomic molecules: anharmonic multimodal vibrational coupling (forming polyads); nonadiabatic coupling between nuclear and electronic coordinates, leading to predissociation. The latter suggests that the polyad vibrational states in the zeroth-order 3p Rydberg manifold are quasi-bound and best understood to be scattering resonances. We observed a rapid dephasing of an initially prepared 'bright' valence state into the relatively long-lived 3p Rydberg state whose multimodal vibrational dynamics and decay we monitor as a function of time. Our quantum simulations, based on an effective spectroscopic Hamiltonian, describe the essential features of the multimodal Fermi resonance-driven vibrational dynamics in the 3p state. We also present evidence of polyad-specificity in the state-dependent predissociation rates, leading to free atomic and molecular fragments. We emphasize that a quantum molecular movie is required to visualize wavepacket dynamics in the 3pσ2Σu Rydberg state of NO2.

Delocalized excitons and interaction effects in extremely dilute thermal ensembles.

Long-range interparticle interactions are revealed in extremely dilute thermal atomic ensembles using highly sensitive nonlinear femtosecond spectroscopy. Delocalized excitons are detected in the atomic systems at particle densities where the mean interatomic distance (>10 µm) is much greater than the laser wavelength and multi-particle coherences should destructively interfere over the ensemble average. With a combined experimental and theoretical analysis, we identify an effective interaction mechanism, presumably of dipolar nature, as the origin of the excitonic signals. Our study implies that even in highly-dilute thermal atom ensembles, significant transition dipole-dipole interaction networks may form that require advanced modeling beyond the nearest neighbor approximation to quantitatively capture the details of their many-body properties.

Integrating Metal-Phenolic Networks-Mediated Separation and Machine Learning-Aided Surface-Enhanced Raman Spectroscopy for Accurate Nanoplastics Quantification and Classification.

Increasing accumulation of nanoplastics across ecosystems poses a significant threat to both terrestrial and aquatic life. Surface-enhanced Raman scattering (SERS) is an emerging technique used for nanoplastics detection. However, the identification and classification of nanoplastics using SERS faces challenges regarding sensitivity and accuracy as nanoplastics are sparsely dispersed in the environment. Metal-phenolic networks (MPNs) have the potential to rapidly concentrate and separate various types and sizes of nanoplastics. SERS combined with machine learning may improve prediction accuracy. Herein, we report the integration of MPNs-mediated separation with machine learning-aided SERS methods for the accurate classification and high-precision quantification of nanoplastics, which is tailored to include the complete region of characteristic peaks across diverse nanoplastics in contrast to the traditional manual analysis of SERS spectra on a singular characteristic peak. Our customized machine learning system (e.g., outlier detection, classification, quantification) allows for the identification of detectable nanoplastics (accuracy 81.84%), accurate classification (accuracy > 97%), and sensitive quantification of various types of nanoplastics (polystyrene (PS), poly(methyl methacrylate) (PMMA), polyethylene (PE), and poly(lactic acid) (PLA)) down to ultralow concentrations (0.1 ppm) as well as accurate classification (accuracy > 92%) of nanoplastic mixtures at a subppm level. The effectiveness of this approach is substantiated by its ability to discern between different nanoplastic mixtures and detect nanoplastic samples in natural water systems.

Adaptive multiscale regression for reliable Raman quantitative analysis.

This paper presents a novel methodology, adaptive multiscale regression (AMR), to adaptively process Raman spectra for quantitative analysis. The proposed methodology aims to construct an optimal calibration model for a Raman spectrum at hand, regardless of its structural characteristics, thus facilitating the application of Raman spectroscopy as a general tool for analytical chemistry. AMR firstly splits the spectra in a calibration set into frequency components at different scales using adaptive wavelet transform (AWT). Parallel member models constructed at different scales are then fused into a final prediction. The contributions of member models to a fusion model are straightforwardly estimated by a partial least square (PLS) model that emerges from a cross-validation results matrix (X) and reference values (Y). This procedure avoids information leakage by fully utilizing the multiscale nature of the input Raman spectra instead of arbitrarily removing some part of the spectral information by calibrating to selected features. Theoretically, we establish that AMR represents an automatic data-driven strategy that captures the Raman spectral structures adaptively and accurately. Our work tests and refines the AMR method by drawing upon the systematic analysis of spectra formulated to yield challenges representative of those encountered in common Raman analyses. AMR compares favorably with other popular preprocessing methods. Satisfactory calibration results suggest that AMR has the capacity to improve robustness and reliability of Raman spectral analysis, and may well extend to other spectroscopic techniques.

The np Rydberg series of boron monohydride: l-uncoupling and its evolution for intermediate principal quantum numbers n = 4 to n = 11.

Using optical-optical-optical triple-resonance spectroscopy, we assign rotational levels with N = 0-5 in the vibrationless, lower-n, p Rydberg states of (11)BH. We apply the Hill and Van Vleck formulation for energy levels with l = 1 in a Hund's case intermediate between (b) and (d) to gauge the energy separating (1)Π and (1)Σ(+) states with zero rotation for n = 4-11. This energy difference, A(l, ξ), represents the strength of the coupling, ξ, between the electron orbital angular momentum, l, and the internuclear axis, which determines the Λ-splitting constant, q(0). The np series exhibits a large q(0) that increases monotonically with n to reach a magnitude similar to the rotational constant, B(0), by n = 9. For higher principal quantum numbers, Λ ceases to be a good quantum number, and l-uncoupling becomes virtually complete for n > 10.

The np Rydberg series of boron monohydride: l-uncoupling and Rydberg electron interactions with the rovibrational motion of the ion core.

A simple two-channel quantum defect theory approach accounts for resonance positions in the np Rydberg series of (11)BH. The transition from Hund's case (b) to (d) in the interacting levels of this np series represents a fundamental example of electron orbital ⇔ cation core rotational coupling, and frame transformation theory offers a means to connect close-coupled electronically excited-state potentials and l-uncoupled Rydberg positions. This evolving interaction of the np Rydberg electron with the rotational and the vibrational motion of the (11)BH(+) core is formulated in terms of quantum defects, µ(λ)(v(+)).

Detecting influential observations by cluster analysis and Monte Carlo cross-validation.

The detection of influential observations is an essential step for building high performance models and has been recognized as an important and challenging task in many industrial and laboratorial applications. A new approach for detecting influential observations is developed based on their effect on partial least squares (PLS) modeling. In this method, we build a large number of PLS models by using Monte Carlo cross-validation (MCCV), and then perform principal component analysis (PCA) on the regression coefficients of these models. Because a model with influential observations is different from the one without influential observation, the series of PLS models cluster into different groups in principal component (PC) spaces, based on the different number of influential observations they contain. The influential observations can be therefore recognized according to the frequency number of each sample in each group. By three examples quantitatively modeling near-infrared (NIR) and Raman spectra, it was shown that the method can detect the influential observations intuitively and veraciously.

Monitoring of mannitol phase behavior during freeze-drying using non-invasive Raman spectroscopy.

In this study, the feasibility of using Raman spectroscopy as a fast, non-invasive, non-destructive technique to monitor crystallization and polymorphic transformations during freeze-drying is assessed using mannitol as the model compound. In-line process monitoring was achieved by interfacing a Raman spectrometer with a fiber-optically coupled, long-working-distance probe to a freeze-drier. By analyzing the process data using principal component analysis, it was possible to extract valuable information pertaining to ice and mannitol crystallization points, the polymorphic form of mannitol, and dehydration of the mannitol hydrate. In conclusion, Raman spectroscopy is a potentially useful technique to monitor physical changes during freeze-drying.

On-line content uniformity determination of tablets using low-resolution Raman spectroscopy.

Analytical techniques for rapid and nondestructive content uniformity determination of pharmaceutical solid dosage forms have been studied for several years in an effort to replace the traditional wet chemistry procedures, which are labor intensive and time consuming. Both Raman spectroscopy and near-infrared spectroscopy have been used for this purpose, and predictability errors are approaching those of the traditional techniques. In this study, a low-resolution Raman spectrometer was utilized to demonstrate the feasibility of both rapid at-line and on-line determination of tablet content uniformity. Additionally, sampling statistics were reviewed in an effort to determine how many tablets should be assayed for specific batch sizes. A good correlation was observed between assay values determined by high-performance liquid chromatography and Raman analysis. Due to rapid acquisition times for the Raman data, it was possible to analyze far more samples than with wet chemistry methods, leading to a better statistical description of variation within the batch. For at-line experiments, the sampling volume was increased by rotating the laser beam during the acquisition period. For the on-line experiments, the sampling volume was increased by sampling from a stream of tablets moving underneath the Raman probe on a conveyor system. Finally, an approach is proposed for monitoring content uniformity immediately following the compaction process. In conclusion, Raman spectroscopy has potential as a rapid, nondestructive technique for at- or on-line determination of tablet content uniformity.

Raman spectroscopy for tablet coating thickness quantification and coating characterization in the presence of strong fluorescent interference.

We report a novel approach to the measurement of colored tablet coating thickness, which employs Raman spectroscopy with univariate and multivariate data analysis. Our results suggest that Raman sensing can serve as a viable non-invasive means to quantify tablet coating thickness in the presence of a fluorescent ingredient in the coating formulation (food colorant Alphazurine FG or D&C Blue No. 4). This study comparatively tests the advantage of several data transformation approaches, including mean centering, standard normal variate, and Savitzky-Golay smoothed second derivative as means of improving predictive models in the presence of fluorescence. By application of the partial least squares (PLS) calibration algorithm to establish optimum covariance between transformed spectral data and measured tablet coating thicknesses, we have been able to create predictive models with calibration errors as small as 4 microm for a training set that spans colored coating thicknesses from 50 to 151 microm.

Raman spectroscopic measurement of tablet-to-tablet coating variability.

We report new results suggesting the feasibility of Raman spectrometry as a tool by which to examine the variability of tablet coatings. Our experiments feature a probe that can operate with a revolving laser focus to average content and coating non-uniformity. Raman spectral changes are correlated with tablet exposure times in a pan coater by means of partial least squares (PLS) multivariate analysis. Statistical models are found to be improved by pre-processing schemes that emphasize spectral changes while minimizing the effects of background light scattering and fluorescence. These pre-processing techniques include multiplicative scatter correction (MSC) and standard normal variate (SNV) transformation, used in concert with Savitzky-Golay second derivative smoothing (SGSD). The two approaches give comparable results yielding R2 values for PLS calibration and cross-calibrated prediction variance regression of 0.999 and 0.997, respectively. Correlation results and model residual values demonstrate that Raman spectroscopy serves sensitively to reflect the coating thickness of the tablets studied.

Dynamics of dissociative recombination versus electron ejection in single rovibronic resonances of BH.

Optical-optical-optical triple resonance spectroscopy isolates transitions to vibrationless Rydberg states of BH with principal quantum numbers from n=7 to 50. Corresponding resonances appear in the excitation spectrum of excited boron atoms produced by the dissociative relaxation of these states. The decay to neutral products occurs on a nanosecond time scale. Yet, corresponding resonances show Fano coupling widths that approach 1 cm-1. Above threshold, spontaneous ionization dominates, but line shapes match for resonances with the same electron orbital quantum numbers built on v+=0 and v+=1 cores. This striking feature-for-feature similarity in predissociation and autoionization line shapes affirms that inelastic electron-cation scattering pathways leading to electron ejection and dissociative recombination proceed through a common continuum.